Explore topic-wise MCQs in Technical MCQs.

This section includes 10 Mcqs, each offering curated multiple-choice questions to sharpen your Technical MCQs knowledge and support exam preparation. Choose a topic below to get started.

1.

Can we solve the multiclass classification problems using Logistic Regression?

A. Yes
B. No
C. Can be yes or no
D. Can not say
E.
Answer» B. No
2.

What are the disadvantages of Logistic Regression?

A. Sometimes a lot ofFeature Engineeringis required
B. It is quite sensitive tonoiseandoverfitting
C. Both A and B
D. None of the above
Answer» D. None of the above
3.

Mean Square Error (MSE) is suitable for Logistic Regression.

A. TRUE
B. FALSE
C. Can be true or false
D. Can not say
Answer» B. FALSE
4.

0 and 1, or pass and fail or true and false is an example of?

A. Multinomial Logistic Regression
B. Binary Logistic Regression
C. Ordinal Logistic Regression
D. None of the above
Answer» C. Ordinal Logistic Regression
5.

Which of the following are advantages of the logistic regression?

A. Logistic Regression is very easy to understand
B. It requires less training
C. It performs well for simple datasets as well as when the data set is linearly separable
D. All of the above
Answer» E.
6.

SVM is insensitive to individual samples.

A. Yes
B. No
C. Can be yes or no
D. Can not say
Answer» B. No
7.

_______ are defined as the ratio of the probability of an event occurring to the probability of the event not occurring.

A. Simple
B. Even
C. Regex
D. Odds
Answer» E.
8.

_________ the target variable can have three or more possible values without any order.

A. Multinomial Logistic Regression
B. Binary Logistic Regression
C. Ordinal Logistic Regression
D. All of the above
Answer» B. Binary Logistic Regression
9.

How many different types of Logistic Regression?

A. 2
B. 3
C. 4
D. 5
Answer» C. 4
10.

Which of the following is used where the target variable is of categorical nature?

A. Keras
B. Knime
C. Logistic Regression
D. MXNet
Answer» D. MXNet